Methods for quality data extraction, alignment, and reporting

ABSTRACT

A method according to a set of instructions stored on the memory of a computing device includes receiving from a plurality of measure storage devices, by a processor of the computing device, a plurality of measures pertaining to at least one patient and at least one clinical measure of the at least one patient. The plurality of measure storage devices are associated with at least one of a plurality of healthcare providers. The method further includes determining, by the processor, a patient-centered quality measure indicating quality across the plurality of healthcare providers with respect to the at least one patient and the at least one clinical measure.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application62/380,689 filed on Aug. 29, 2016.

BACKGROUND

Measuring quantifiable data is widely practiced throughout the world.Measurements can be used in many various industries and for many variouspurposes. For example, measurements may be utilized in industries suchas health care, banking, finance, retail, services, or any otherindustry. Measurements may also be kept or stored in various ways. Forexample, measurements may be stored physically in files orelectronically on cloud storages, document management systems, secureservers, hard drives, etc.

In just one example, measurements are utilized in the health careindustry for various purposes. For example, a health care provider maymeasure a patient's vitals, presence of chemicals, or any other type ofmeasurement. Such measurements may be used to understand a patient'shealth, and may be further used by an insurance provider of the patientor another third party payee such as a government agency.

Measurements are important to many individuals, businesses, andgovernments. Accordingly, measurements are the subject of much attentionwith regards to how measurements are identified, aggregated, classified,prioritized, stored, secured, archived, preserved, retrieved, tracked,destroyed, and otherwise used. Decisions based on such measurements aremade based on many different factors including applicable laws, companypolicies, expected future utilization of a measurement, type ofmeasurement, importance/value of a measurement, etc.

Heretofore, conventional healthcare delivery and payment systems arevolume-based in that the more volume a physician or medical careprovider has, the higher their reimbursement. Rewarding physicians orother medical providers for volume instead of quality of outcome resultsin unwanted and inefficient outcomes. In an effort to shift qualitybased delivery, federal and state governments are requiring qualityreporting on quality measures. Such reporting may include hundreds ofquality measures.

Another challenge with conventional healthcare delivery and paymentsystems includes reporting measures that are “provider-centric” whichassess provider performance on the measures reported. Thisprovider-centric approach does not necessarily correlate to improvedoutcomes for patients. In fact, the provider-centric approach enablesproviders and clinics to “game” the system to report high “scores” ontheir quality measures to insure maximum financial reward regardless ofthe outcome for the patient under today's quality reporting approach.Further, conventional “provider-centric” quality measuring and reportingtypically involves the actions of only one provider in one care settingfor each patient whereas in reality many patients visit multipleproviders in multiple settings of care. Compounding the problem, mostconventional electronic health record (EHR) vendors do not adhere astandard national format for quality reporting and many HER vendorscannot yet generate many of the national quality measures required byfederal programs.

SUMMARY

Described embodiments herein capture quality measures for one patient inmultiple settings of care (across multiple providers) and roll themeasures up into one combined quality measure for that patient. Such asystem provides patient-centric quality measurement and does correlateto improved outcomes for a single patient. Furthermore, disclosedembodiments also can take the quality measures for multiple patients inmultiple settings of care (with multiple providers) and roll those upinto a “population-centric” quality measurement that is correlated toimproved outcomes for multiple patients in a population, thus helpingimprove population health. For example, one embodiment obtains data formultiple patients in a patient population that have common health issues(high incidence rate of diabetes) and determines how they scored onmeasures related to diabetes in every care setting whether they were indifferent clinics, cities or even different states and see how they allcompare one quality measure. An illustrative embodiment strictly usesstandards for quality measure information thus allowing fullinteroperability for quality measure reporting where none exists today.

Described embodiments herein find and combine all data necessary tocompute quality measures. Conventional EHR systems are unable to do so,resulting in very high expenses for those vendors who achieve even avery basic level of success in quality reporting. For example,calculating a quality measure related to screening for breast cancer notonly requires data that the EHR vendor has readily available from thein-clinic screening by the doctor, but this measure also requires datathat can only be found in an electronic “lab result” and this lab resultinformation is not easily accessible by the vast majority of HERsystems; it typically resides in different places. The necessity offinding and integrating data from disparate sources is a major componentto the difficulty and expense incurred by EHR vendors trying tocalculate and report quality measures. To compound this matter, thefederal government typically changes significant portions of the qualityreporting requirements every year.

Described embodiments herein provide common, centralized qualityreporting destinations. These embodiments improve the behavior of theproviders but more importantly improve the health of the patient (e.g.improve outcomes). The described embodiments move away from volume-baseddelivery and payment to quality-based delivery and payment. Thedescribed embodiments provide a more sustainable system that the currentvolume-based healthcare system.

An illustrative method according to a set of instructions stored on thememory of a computing device includes receiving from a plurality ofmeasure storage devices, by a processor of the computing device, aplurality of measures pertaining to at least one patient and at leastone clinical measure of the at least one patient. Each of the pluralityof measure storage devices are associated with at least one of aplurality of healthcare providers. The method further includesdetermining, by the processor, a patient-centered quality measureindicating quality across the plurality of healthcare providers withrespect to the at least one patient and the at least one clinicalmeasure.

An illustrative method according to a set of instructions stored on thememory of a computing device includes receiving from a plurality ofmeasure storage devices, by a processor of the computing device, aplurality of measures pertaining to a plurality of patients and at leastone clinical measure of the plurality of patients. Each of the pluralityof measure storage devices are associated with at least one of aplurality of healthcare providers. The method further includesdetermining, by the processor, a population-centered quality measureindicating quality across the plurality of healthcare providers withrespect to the plurality of patients and the at least one clinicalmeasure.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments will hereafter be described with reference tothe accompanying drawings.

FIG. 1 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including generating a patient-centeredquality measure in accordance with an illustrative embodiment.

FIG. 2 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including generating a population-centeredquality measure in accordance with an illustrative embodiment.

FIG. 3 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including sending data to payers in accordancewith an illustrative embodiment.

FIG. 4 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including extracting and converting data inaccordance with an illustrative embodiment.

FIG. 5 is a block diagram illustrating an example computer 500 inaccordance with an illustrative embodiment.

DETAILED DESCRIPTION

Disclosed herein are systems and methods, which can be realized insoftware, hardware, or a combination thereof, to perform quality dataextraction, alignment, and reporting. Quality data and quality measureextraction, alignment, and reporting are useful in industries wherecontinuous quality improvement is applied, such as manufacturing,energy, or healthcare. In healthcare for example, various types ofquality measures have been established for determining the quality ofcare that healthcare providers deliver to their patients, and healthplans/payers are shifting to payment models that reward providers basedon higher quality of care delivered to the health plan's members.Advantageously, the methods and systems disclosed herein provide forextracting, calculating, aligning, and reporting quality information.Further, current quality measurements are provider-centric. The methodsand systems disclosed herein advantageously demonstrate howpatient-centric, as opposed to provider-centric, quality information maybe extracted, calculated, and aligned. Current quality reportingincludes methods and formats that vary widely by provider and payer andinvolve costly and inefficient point-to-point connections between everyprovider and every payer nationally, and provider payments from payerscan be affected by the provider's quality ratings. Disclosed herein aremethods and systems for a single method and service for transportingquality data in standard formats, extracting quality information fromthat data to calculate measures, aligning measures for one patient inmultiple care settings and for populations of patients thereby offeringadvantageous ways for performing patient-centric quality measurement,and for reporting such quality measures to health plans and payers,including state and federal government payers such as Medicaid andMedicare. This methods and systems disclosed herein are not limited toimprovement in healthcare, but can be used for quality measurement andquality reporting in any industry where continuous quality improvementis needed.

In various healthcare related embodiments, a method is initiated when aCertified Electronic Health Record Technology (CEHRT) used by ahealthcare provider when recoding information during a patient visitsends one file containing quality information in a standard format (Q1)for one patient (P1) for that one electronic health record (EHR) (E1)for one quality measure (M1)—referred to as Q1P1E1M1. Another providerseeing that same patient (P1) in a different setting might be using adifferent EHR (E2) and would send one quality measure in the same format(Q1) for the same measure (M1)—referred to as Q1P1E2M1. When a system asdisclosed herein receives Q1P1E1M1, Q1P1E2M1, and conceivably any filescontaining the same measure (M1) for that patient (P1) from any numberof additional EHRs and care settings (En), notated as Q1P1EnM1, thesystems and methods can then: (1) align and roll-up all Q1P1M1 from anyEHR/care setting (Ex) by treating the EHR number as a “don't care”giving Q1P1ExM1, resulting in a patient-centric quality measure; and (2)align and roll-up all Q1ExM1 for a population of n patients (P1 . . . n)to resulting in a population-centric quality measure.

The systems and methods disclosed herein work for any number ofpatients, EHRs/care settings, and quality measures, of which there arehundreds or more (denoted Q1PnEnMi). The systems and methods disclosedherein also work for other formats, such as payer proprietary formats,BPnEnMi. For example, the system can utilize, read, convert, extract,incorporate, etc. various reporting formats, such as Quality ReportingDocument Architecture (QRDA), Blue Care Networks (BCN), Semanticclinical Drug Form (SCDF), or Continuity of Care Document (CCD) formats.In some embodiments, different or additional formats may be used. Insome embodiments, a system includes an extractor where providers sendquality data in a first format and it is extracted to one or moreformats for various uses such as quality reports and/or sending topayers. For example, a system can include a BCN to QRDA extractor whereproviders send quality data in a BCN format. The BCN to QRDA extractorcan therefore extract Q1 formatted data from BCN (B) formatted data toconvert BCN (B) to QRDA 1 (Q1) to generate quality reporting. The QRDAdata that has been extracted may also be sent to payers. After allprocessing, quality measures can be reported to health plans/payers in aQRDA 1 (Q1) format, or other format as desired. Further embodiments aredescribed below with respect to the figures.

FIG. 1 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including generating a patient-centeredquality measure in accordance with an illustrative embodiment. Inalternative embodiments, fewer, additional, and/or different componentsmay be present. The system 100 includes practices and providers that useelectronic health records (EHR) systems 102, 104, 106, and 108. The EHRs102, 104, 106, 108 may be similar or different EHR systems. In this way,different types of EHRs can send quality reporting data within thesystem, and the system can align data from any type ofEHR/practice/provider. In the system 100, the EHRs 102, 104, 106, 108generate data in the QRDA format.

The EHR 102 generates report Q1P1E1M1, indicating QRDA data (Q1) for afirst patient (P1), from the first EHR 102 (E1), about a first measure(M1). A measure may be any type of healthcare reporting data. Forexample, M1 may related to blood pressure, temperature, weight, etc. Atthe time of writing hundreds of standard measures are recorded andreported in EHRs by practices and providers that can be sent and usedfor quality reporting. The systems and methods herein can be adapted toaccommodate as many or as few measures as desired, including measuresthat are not currently recorded and reported today. Any number of othermeasures that can be reported with respect to the first patient areindicated in the system 100 as Q1P1E1Mn. Similar data can be generatedon the first patient from the other EHRs 104, 106, and 108. Such datahas different E designations indicating the EHR it came from (e.g., E2,E3, En). The EHR 108 (En) represents that there can be any number ofpossible EHRs sending measures information. In some embodiments,multiple providers may use the same EHR. In some embodiments, a singlepayer may use multiple EHRs.

Measure data can be sent from the EHRs 102, 104, 106, 108 at a step 110to a quality data processing system 112. At the quality data processingsystem 112, data can be extracted, aligned, and reported as disclosedherein throughout. For example, at a data extractor 114, the system canextract data 116 that is related to the first measure (M1), regardlessof what EHR the data came from (denoted by Ex). In this way, all thedata on the first patient (P1) related to the first measure (M1) can beextracted and aligned for a patient-centered quality measure 118. Inthis way, no matter which practices and providers a patient has visited,data related to the first measure (M1) can be assembled for an inclusivereport on that first patient (P1). Similarly, data (Q1P1ExMn) for anyother measure (Mn) can be assembled for the first patient (P1) and usedfor the patient-centered quality measure 118.

The quality data processing system 112 also includes aspects 120 of ahealth provider directory (HPD), active care relationship service(ACRS), and a common key service (CKS). Such aspects 120 can assist inreporting. For example, the HPD can used to keep track of which EHRs areassociated with specific health care providers and information aboutthose providers. In another example, the ACRS can be used to keep trackof information relating to particular patients, such as demographicinformation. In another example, the CKS can be used to identifypatients anonymously and uniquely, such that their data is protected butstays organized and separate from other patients. U.S. patentapplication Ser. No. 14/643,910, filed on Mar. 10, 2015, is incorporatedherein by reference, and describes various aspects of a CKS system thatmay be utilized in combination with the systems and methods disclosedherein.

FIG. 2 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including generating a population-centeredquality measure in accordance with an illustrative embodiment. Inalternative embodiments, fewer, additional, and/or different componentsmay be present. The system 200 includes additional data for a secondpatient (P2) and any number of additional patients (Pn) from each of theEHRs 102, 104, 106, 108. For example, the system 200 shows a measure(Q1P2E1M1) in QRDA format (Q1) for a second patient (P2), from the EHR102 (E1), and relating to the first measure (M1). The measure(s) fromthe EHR 102 can include any number of measure for any number of otherpatients as shown by Q1PnE1Mn. The other EHRs 104, 106, and 108 showsimilar measures for the second and additional patients.

Such data can be sent to a quality data processing system 224, where adata extractor 226 can extract data 220 for population-centered qualitymeasure reporting 222. For example, information in a QRDA format (Q1)can be extracted for a population (P1 . . . n) from any EHR (Ex) for afirst measure (M1): Q1P1 . . . nExM1. A population can be selected to beall of the patients that have a particular measure reported, or may beselected based on any other category. For example, a population may beany patient who has visited a practice or provider in a certain healthsystem, any patient that matches a certain demographic, any patient witha particular diagnosis, or any other type of population or combinationsof populations. Thus, with the data Q1P1 . . . nExM1 reports can beassembled that indicate quality for a given population with respect to afirst measure. Similarly, population-centered quality measures 222 maybe assembled for any other populations or combinations of populationsbased on one or more different measure, as represented by Q1P1 . . .nExMn.

The HPD, ACRS, and CKS of 120 can also be used for rolling up differenttypes of quality reports efficiently storing, sorting, and keeping trackof data for those various reports. For example, selecting differenttypes of populations to run reports on may be assembled by filtering forcertain demographics of patients, such as location, age, gender, etc.Other types of reports may be done to focus on populations that visitcertain providers, or reports that are focused on patients that visitproviders with a particular EHR. Population reports for patientsdiagnosed similarly may also be run. Other types of reports based onvarious specific characteristics of a population are also contemplatedherein.

FIG. 3 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including sending data to payers in accordancewith an illustrative embodiment. In alternative embodiments, fewer,additional, and/or different components may be present. The system 300shows how data extracted by a data extractor 336 of a quality dataprocessing system 334 can also be sent payers 330, in addition extracteddata being used to generate patient- and population-centered qualitymeasures 118 and 222.

The data extractor 336 extracts data 326 related to a first patient(P1), a second patient (P2), and any other patients (Pn) that a payer330 may use to determine quality measures (M1, Mn) and/or pay thepractices/providers shown in FIGS. 1 and 2. Accordingly, the data 326for any patient from any EHR related to any measure can be extracted asindicated by Q1PnEnMn. Such data 336 can be sent at 328 to variouspayers 330. The aspects 120 including the HPD, ACRS, and CKS may beutilized to determine what data 326 to send to particular payers 330.

FIG. 4 is a diagram illustrating a system for quality data extraction,alignment, and reporting, including extracting and converting data inaccordance with an illustrative embodiment. In alternative embodiments,fewer, additional, and/or different components may be present. Thesystem 400 shows an example where quality reporting data from EHRs is ina BCN format and converted into QRDA data formats. In variousembodiments, any format may be used to send data from the EHRs and thatdata can be converted to any other type of format. For example, datafrom the first EHR relating to various patients (P1, P2, Pn) for variousmeasures (M1, Mn) are included in BCN format measures, shown asBCNPnE1Mi. Similarly, data from the other EHRs is also sent in a BCNformatted measure, including data from EHR2, EHR3, and any other EHRs(EHRn).

The data from the EHRs is sent to a BCN to QRDA extractor 446 of aquality data processing system 444. The BCN to QRDA extractor 446 canextract QRDA data from the BCN data for use in assembling patient-and/or population-centered quality measure reports 118 and 222 asdisclosed herein. The BCN to QRDA Extractor 446 can also extract QRDAdata 438 to be sent in QRDA format 440 to payers 330. Therefore, thequality data processing system 444 has value where providers or EHRssend measure data that is in a different format than data that should besent to payers. Similarly, data sent to a quality data processing system444 can still be extracted and used to assemble patient- and/orpopulation-centered quality measure reports 118 and 222.

In some embodiments a quality data processing system may receive measuredata in various different formats (BCN, QRDQ, etc.), and various dataextractors may be used to extract data into any number of formats asdesired by payers and to assemble various patient- andpopulation-centered quality measures. Accordingly, any type of formatused by a payer, provider, EHR, etc. can be accommodated by the system.Similarly, any type or format of data received can be extracted,aligned, and used for quality reporting.

The systems of FIGS. 3 and 4 enable the capture of quality measures fora patient in multiple settings of care (across multiple providers).These systems can roll the measures up into one combined quality measurefor that patient. Such systems provides patient-centric qualitymeasurement that can correlate to improved outcomes for a singlepatient. The systems also can take the quality measures for multiplepatients in multiple settings of care (with multiple providers) and rollthose up into a “population-centric” quality measurement that iscorrelated to improved outcomes for multiple patients in a population,thus helping improve population health. For example, one embodimentobtains data for multiple patients in a patient population that havecommon health issues (high incidence rate of diabetes) and determineshow they scored on measures related to diabetes in every care settingwhether they were in different clinics, cities or even different statesand see how they all compare one quality measure. An illustrativeembodiment strictly uses standards for quality measure information thusallowing full interoperability for quality measure reporting where noneexists today.

Calculating a quality measure related to screening for breast cancer notonly requires data that the EHR vendor has readily available from thein-clinic screening by the doctor, but this measure also requires datathat can only be found in an electronic “lab result” and this lab resultinformation is not easily accessible by the vast majority of HERsystems; it typically resides in different places. The necessity offinding and integrating data from disparate sources is a major componentto the difficulty and expense incurred by EHR vendors trying tocalculate and report quality measures. The systems of FIGS. 3 and 4common, centralized quality reporting destinations. These systemsimprove the behavior of the providers but more importantly improve thehealth of the patient (e.g. improve outcomes). Advantageously, thesystems move away from volume-based delivery and payment toquality-based delivery and payment.

FIG. 5 is a block diagram illustrating an example computer 500 inaccordance with an illustrative embodiment. In alternative embodiments,fewer, additional, and/or different components may be present. Thecomputer 500 may be any computing machine, such as a tablet, smartphone, laptop computer, desktop computer, server, remote client device,gaming device, smart television device, wearable computer, or anycombination thereof. The computer 500 includes at least one processor502 coupled to a chipset 504. The chipset 504 includes a memorycontroller hub 520 and an input/output (I/O) controller hub 522. Amemory 506 and a graphics adapter 512 are coupled to the memorycontroller hub 520, and a display 518 is coupled to the graphics adapter512. A storage device 508, keyboard 510, pointing device 514, andnetwork adapter 516 are coupled to the I/O controller hub 522. Otherembodiments of the computer 500 may have different architectures.

The storage device 508 is a non-transitory computer-readable storagemedium such as a hard drive, compact disk read-only memory (CD-ROM),DVD, or a solid-state memory device. The memory 506 holds instructionsand data used by the processor 502. The pointing device 514 is a mouse,track ball, or other type of pointing device, and is used in combinationwith the keyboard 510 to input data into the computer 500. The pointingdevice 514 may also be a gaming system controller, or any type of deviceused to control the gaming system. For example, the pointing device 514may be connected to a video or image capturing device that employsbiometric scanning to detect a specific user. The specific user mayemploy motion or gestures to command the point device 514 to controlvarious aspects of the computer 500.

The graphics adapter 512 displays images and other information on thedisplay 518. The network adapter 516 couples the computer system 500 toone or more computer networks.

The computer 500 is adapted to execute computer program modules forproviding functionality described herein. As used herein, the termmodule refers to computer program logic used to provide the specifiedfunctionality. Thus, a module can be implemented in hardware, firmware,and/or software. In one embodiment, program modules are stored on thestorage device 508, loaded into the memory 506, and executed by theprocessor 502.

The types of computers used by the entities and processes disclosedherein can vary depending upon the embodiment and the processing powerrequired by the entity. The computer 500 may be a mobile device, tablet,smartphone or any sort of computing element with the above-listedelements. For example, a data storage device, such as a hard disk, solidstate memory or storage device, might be stored in a distributeddatabase system comprising multiple blade servers working together toprovide the functionality described herein. The computers can lack someof the components described above, such as keyboards 510, graphicsadapters 512, and displays 518.

The computer 500 may act as a server. The computer 500 may be clusteredwith other computer 500 devices to create the server. The variouscomputer 500 devices that constitute the server may communicate witheach other over a network.

As would be appreciated by one of ordinary skill in the art, theembodiments disclosed herein may be implemented on any system, networkarchitecture, configuration, device, machine, or apparatus, and is notto be construed as being limited to any specific configuration, network,or systems, even though an example system is shown and described withrespect to FIG. 5. The embodiments herein may be suitably implemented onconventional computing devices, for example, computer workstations, onInternet based applications, on optical computing devices, neuralcomputers, biological computers, molecular computing devices, and otherdevices. As may be appreciated by those skilled in the art, the presentinvention, in short, may be implemented on any system, automaton, and/orTuring machine.

An automaton is herein described as a mechanism that is relativelyself-operating and designed to follow a predetermined sequence ofoperations or respond to encoded instructions. A Turing machine isherein described as an abstract expression of a computing device thatmay be realized or implemented on an infinite number of differentphysical computing devices. Examples of systems, automatons and/orTuring machines that may be utilized in performing the process of thepresent invention include, but are not limited to: electrical computers(for example, an International Business Machines (IBM) personalcomputer); neuro-computers (for example, one similar to the “GeneralPurpose Neural Computer” described in U.S. Pat. No. 5,155,802, issued toPaul H. Mueller, on Oct. 13, 1992); molecular computers (for example,one similar to the “Molecular Automata Utilizing Single or Double-StrandOligonucleotides” described in U.S. Pat. No. 5,804,373, issued to AllanLee Schweiter et al., on Sep. 8, 1998); biological computers (forexample, one similar to the biological computer presented by EhudShapiro, of the Computer Science and Applied Mathematics Department atthe Weizman Institute of Science (Rehovot, Israel), at the FifthInternational Meeting on DNA-Based Computers); and optical computers.For purposes of simplicity, such devices hereinafter are referred to ascomputers, as is commonly understood in the art. But, the embodimentsdisclosed herein are not limited being applied to such devices and maybe accomplished upon any system or collection of systems capable ofproviding the features and functions identified herein.

The methods and systems described above and below with respect to FIGS.1-4 may be performed partially or wholly on a processor, such as the onedescribed above with regards to computer 500.

Certain of the devices shown in FIG. 5 include a computing system. Thecomputing system includes a processor (CPU) and a system bus thatcouples various system components including a system memory such as readonly memory (ROM) and random access memory (RAM), to the processor. Theaspects disclosed herein may be suitably implemented on conventionalcomputing devices, for example, computer workstations, on Internet basedapplications, on optical computing devices, neural computers, biologicalcomputers, molecular computing devices, and other devices. As may beappreciated by those skilled in the art, the aspects disclosed hereinmay be implemented on any system, automaton, and/or automated machine.

Other system memory may be available for use as well. The computingsystem may include more than one processor or a group or cluster ofcomputing system networked together to provide greater processingcapability. The system bus may be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. A basicinput/output (BIOS) stored in the ROM or the like, may provide basicroutines that help to transfer information between elements within thecomputing system, such as during start-up. The computing system furtherincludes data stores, which maintain a database according to knowndatabase management systems. The data stores may be embodied in manyforms, such as a hard disk drive, a magnetic disk drive, an optical diskdrive, tape drive, or another type of computer readable media which canstore data that are accessible by the processor, such as magneticcassettes, flash memory cards, digital versatile disks, cartridges,random access memories (RAMs) and, read only memory (ROM). The datastores may be connected to the system bus by a drive interface. The datastores provide nonvolatile storage of computer readable instructions,data structures, program modules and other data for the computingsystem.

To enable human (and in some instances, machine) user interaction, thecomputing system may include an input device, such as a microphone forspeech and audio, a touch sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, motion detection, camera for videoand photo input, and so forth. An output device can include one or moreof a number of output mechanisms, such as a display screen, a printer,or speaker. In some instances, multimodal systems enable a user toprovide multiple types of input to communicate with the computingsystem. A communications interface generally enables the computingdevice system to communicate with one or more other computing devicesusing various communication and network protocols.

Embodiments disclosed herein can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including theherein disclosed structures and their equivalents. Some embodiments canbe implemented as one or more computer programs, i.e., one or moremodules of computer program instructions, encoded on a tangible computerstorage medium for execution by one or more processors. A computerstorage medium can be, or can be included in, a computer-readablestorage device, a computer-readable storage substrate, or a random orserial access memory. The computer storage medium can also be, or can beincluded in, one or more separate tangible components or media such asmultiple CDs, disks, or other storage devices. The computer storagemedium does not include a transitory signal.

As used herein, the term processor encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The processor can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theprocessor also can include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.

A computer program (also known as a program, module, engine, software,software application, script, or code) can be written in any form ofprogramming language, including compiled or interpreted languages,declarative or procedural languages, and the program can be deployed inany form, including as a stand-alone program or as a module, component,subroutine, object, or other unit suitable for use in a computingenvironment. A computer program may, but need not, correspond to a filein a file system. A program can be stored in a portion of a file thatholds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub-programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

To provide for interaction with an individual, the herein disclosedembodiments can be implemented using an interactive display, such as agraphical user interface (GUI). Such GUI's may include interactivefeatures such as pop-up or pull-down menus or lists, selection tabs, andother features that can receive human inputs.

The computing system disclosed herein can include clients and servers. Aclient and server are generally remote from each other and typicallyinteract through a communications network. The relationship of clientand server arises by virtue of computer programs running on therespective computers and having a client-server relationship to eachother. In some embodiments, a server transmits data (e.g., an HTML page)to a client device (e.g., for purposes of displaying data to andreceiving user input from a user interacting with the client device).Data generated at the client device (e.g., a result of the userinteraction) can be received from the client device at the server.

In an illustrative embodiment, any of the operations described hereincan be implemented at least in part as computer-readable instructionsstored on a computer-readable medium or memory. Upon execution of thecomputer-readable instructions by a processor, the computer-readableinstructions can cause a computing device to perform the operations.

The foregoing description of illustrative embodiments has been presentedfor purposes of illustration and of description. It is not intended tobe exhaustive or limiting with respect to the precise form disclosed,and modifications and variations are possible in light of the aboveteachings or may be acquired from practice of the disclosed embodiments.It is intended that the scope of the invention be defined by the claimsappended hereto and their equivalents.

What is claimed is:
 1. A method according to a set of instructionsstored on the memory of a computing device, the method comprising:receiving from a plurality of measure storage devices, by a processor ofthe computing device, a plurality of measures pertaining to at least onepatient and at least one clinical measure of the at least one patient,wherein each of the plurality of measure storage devices are associatedwith at least one of a plurality of healthcare providers; anddetermining, by the processor, a patient-centered quality measureindicating quality across the plurality of healthcare providers withrespect to the at least one patient and the at least one clinicalmeasure.
 2. The method of claim 1, wherein the plurality of measures areformatted according to a Quality Reporting Document Architecture (QRDA)format.
 3. The method of claim 1, further comprising determining onecombined quality measure for the at least one patient.
 4. The method ofclaim 1, further comprising determining quality measures for a pluralityof patients in multiple settings of care with multiple providers.
 5. Themethod of claim 4, further comprising calculating a populating-centricquality measuring outcomes for multiple patients in a population.
 6. Themethod of claim 4, wherein the quality measures are based onstandards-based quality measure information configured to becommunicated to a plurality of systems.
 7. The method of claim 1, wherethe plurality of measures comprise data necessary to compute qualitymeasures.
 8. The method of claim 1, further comprising obtaining datafor multiple patients in a patient population with common health issuesand determining how the multiple patients scored on measures related tothe common health issues in every care setting by clinic, city andstate.
 9. A method according to a set of instructions stored on thememory of a computing device, the method comprising: receiving from aplurality of measure storage devices, by a processor of the computingdevice, a plurality of measures pertaining to a plurality of patientsand at least one clinical measure of the plurality of patients, whereineach of the plurality of measure storage devices are associated with atleast one of a plurality of healthcare providers; and determining, bythe processor, a population-centered quality measure indicating qualityacross the plurality of healthcare providers with respect to theplurality of patients and the at least one clinical measure.
 10. Themethod of claim 9, wherein the plurality of measures are formattedaccording to a Quality Reporting Document Architecture (QRDA) format.11. The method of claim 9, wherein the plurality of measures areformatted according to a Blue Care Network (BCN) format.
 12. The methodof claim 11, further comprising converting the plurality of measuresfrom the BCN format to a Quality Reporting Document Architecture (QRDA)format.
 13. The method of claim 12, further comprising sending theplurality of measures converted to the QRDA format to a plurality ofpayer devices.
 14. The method of claim 9, wherein the plurality ofmeasures comprises a common key that uniquely identifies each of theplurality of patients.
 15. An apparatus comprising: a memory; aprocessor coupled to the memory; and a set of instructions stored on thememory and configured to be executed by the processor, wherein theprocessor is configured to: receive from a plurality of measure storagedevices a plurality of measures pertaining to at least one patient andat least one clinical measure of the at least one patient, wherein eachof the plurality of measure storage devices are associated with at leastone of a plurality of healthcare providers; and determine apatient-centered quality measure indicating quality across the pluralityof healthcare providers with respect to the at least one patient and theat least one clinical measure.
 16. The apparatus of claim 15, whereinthe processor is further configured to determine one combined qualitymeasure for the at least one patient.
 17. The apparatus of claim 15,wherein the processor is further configured to determine qualitymeasures for a plurality of patients in multiple settings of care withmultiple providers.
 18. The apparatus of claim 17, wherein the processoris further configured to calculate a populating-centric qualitymeasuring outcomes for multiple patients in a population.
 19. Theapparatus of claim 17, wherein the quality measures are based onstandards-based quality measure information configured to becommunicated to a plurality of systems.
 20. The apparatus of claim 15,wherein the processor is further configured to obtain data for multiplepatients in a patient population with common health issues and determinehow the multiple patients scored on measures related to the commonhealth issues in every care setting by clinic, city and state.